Revert part the performance optimization (#723) because of #753.
v2.30.0
Add manual sort
Performance improvements (#723)
v2.29.0
Add support for Webpack 3
v2.28.0
Backport 3.x void tag for plugin authors
v2.27.1
Revert 2.25.0 loader resolving
v2.27.0
Fix a chunksorter webpack 2 issue (#569)
Fix template path resolving(#542)
v2.26.0
Allow plugins to add attributes without values to the and tags
v2.25.0
Clearer loader output
Add basic support for webpack 2
v2.24.1
Hide event deprecated warning of ‘applyPluginsAsyncWaterfall’ for html-webpack-plugin-after-emit and improve the warning message.
v2.24.0
Update dependencies
Add deprecate warning for plugins not returning a result
Add [path] for favicons
v2.23.0
Update dependencies
Stop automated tests for webpack 2 beta because of #401
v2.22.0
Update dependencies
v2.21.1
Better error handling (#354)
v2.21.0
Add html-webpack-plugin-alter-asset-tags event to allow plugins to adjust the script/link tags
v2.20.0
Exclude chunks works now even if combined with dependency sort
v2.19.0
Add html-webpack-plugin-alter-chunks event for custom chunk sorting and interpolation
v2.18.0
Updated all dependencies
v2.17.0
Add type attribute to script element to prevent issues in Safari 9.1.1
v2.16.2
Fix bug introduced by 2.16.2. Fixes #315
v2.16.1
Fix hot module replacement for webpack 2.x
v2.16.0
Add support for dynamic filenames like index[hash].html
v2.15.0
Add full unit test coverage for the webpack 2 beta version
For webpack 2 the default sort will be ‘dependency’ instead of ‘id’
Upgrade dependencies
v2.14.0
Export publicPath to the template
Add example for inlining css and js
v2.13.0
Add support for absolute output file names
Add support for relative file names outside the output path
v2.12.0
Basic Webpack 2.x support #225
v2.11.0
Add xhtml option which is turned of by default. When activated it will inject self closed tags instead of unclosed tags. https://github.com/ampedandwired/html-webpack-plugin/pull/255
Add support for webpack placeholders inside the public path e.g. '/dist/[hash]/'. https://github.com/ampedandwired/html-webpack-plugin/pull/249
v2.10.0
Add hash field to the chunk object
Add compilation field to the templateParam object (fixes https://github.com/ampedandwired/html-webpack-plugin/issues/237)
Fix an issue where incomplete cache modules were used
v2.4.0
Don’t recompile if the assets didn’t change
v2.3.0
Add events html-webpack-plugin-before-html-processing, html-webpack-plugin-after-html-processing, html-webpack-plugin-after-emit to allow other plugins to alter the html this plugin executes
v2.2.0
Inject css and js even if the html file is incomplete (fixes https://github.com/ampedandwired/html-webpack-plugin/issues/135 )
Update dependencies
v2.1.0
Synchronize with the stable @1 version
v2.0.4
Fix minify option
Fix missing hash interpolation in publicPath
v2.0.3
Add support for webpack.BannerPlugin
v2.0.2
Add support for loaders in templates (fixes https://github.com/ampedandwired/html-webpack-plugin/pull/41 )
Remove templateContent option from configuration
Better error messages
Update dependencies
v1.7.0
Add chunksSortMode option to configuration to control how chunks should be sorted before they are included to the html
Don’t insert async chunks into html (fixes https://github.com/ampedandwired/html-webpack-plugin/issues/95 )
Update dependencies
v1.6.2
Fix paths on Windows
Fix missing hash interpolation in publicPath
Allow only false or object in minify configuration option
v1.6.1
Add size field to the chunk object
Fix stylesheet s being discarded when used with "inject: 'head'"
Update dependencies
v1.6.0
Support placing templates in subfolders
Don’t include chunks with undefined name (fixes https://github.com/ampedandwired/html-webpack-plugin/pull/60 )
Don’t include async chunks
v1.5.2
Update dependencies (lodash)
v1.5.1
Fix error when manifest is specified (fixes https://github.com/ampedandwired/html-webpack-plugin/issues/56 )
v1.5.0
Allow to inject javascript files into the head of the html page
Optionally add webpack hash as a query string to resources included in the HTML
(hash: true) for cache busting
CSS files generated using webpack (for example, by using the
extract-text-webpack-plugin)
are now automatically included into the generated HTML
More detailed information about the files generated by webpack is now available
to templates in the o.htmlWebpackPlugin.files attribute. See readme for more
details. This new attribute deprecates the old o.htmlWebpackPlugin.assets attribute.
The templateContent option can now be a function that returns the template string to use
Expose webpack configuration to templates (o.webpackConfig)
Sort chunks to honour dependencies between them (useful for use with CommonsChunkPlugin).


Make navs used as navigation accessible. If you are using navs to provide a navigation bar, be sure to add a role="navigation"
to the most logical parent container of the

, or wrap a
element around the whole navigation. Do not add the role to the

itself, as this would prevent it from being announced as an actual list by assistive technologies.
The Stacked Nav is useful as a "left nav" and is designed to to be 100% of the width of its parent grid column. At smaller viewports, each item in the nav will become inline-block
and display in a single wrapping line.

Home

Products

Services

About

Contact

A second level maybe added to the Stacked Nav for additional navigation options. However, at small viewports, the second level is not visible.

Products

Widget

Gizmo

Snarfblat


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Loading error: {{ model.loading_error || 'No error'}}


GHOSTBUSTERS II A film review by Jeff Meyer Copyright 1989 Jeff Meyer
Summing up tag for GHOSTBUSTERS II: "A kinder, gentler Ghostbusters." And to borrow from PR rhetoric, I mean that in the best sense of the term. I found GHOSTBUSTERS II to be an enjoyable, humorous and ultimately entertaining film. It does have a different emphasis than its predecessor, and that seems to be garnering it a good deal of criticism, but I thought that GHOSTBUSTERS II's new outlook worked very well for it, particularly as a sequel.
Let me back up a bit: I've always looked at GHOSTBUSTERS as another production model on the Bill Murray (star)/Harold Ramis (writer)/Ivan Reitman (director) assembly line, a combination of talents who've mixed up some particularly funny films. (STRIPES and GHOSTBUSTERS are the prominent examples.) With GHOSTBUSTERS, they hit a chord from the best of the Marx Brothers movies: characters who were absolutely wacko, but who you were cheering for at the same time. The opera scene at the end of A NIGHT AT THE OPERA; The Boys vs. Zuhl. You're laughing at them, and with them, and at the same time, you're going "rah-rah" with the rabbis and priests and NYC residents outside. (Well, I was...)
GHOSTBUSTERS II concentrates a dollop more on the characters it introduced in the first film, not a bad thing for a sequel; its lower intensity results in a lower major-guffaw hit ratio than its predecessor, but it's a trade that I was willing to accept. The Boys have a comfortable feel around them this time out; if they don't build the story up for as many full-tilt laughs as before, it's because they're getting laughs through the intricacies and foibles of their characters. Ray's cheery optimism (and his enjoyment of Peter's schemes), Igon's cold amusement and his little experiments, and Venkeman's Game Show Host personality are all played around with more -- less amplitude, but more fine-tuning. And they all parody their mock-heroic image throughout. ("Suck up your guts, boys; The Ghostbusters are here.") Peter's character (Bill Murray) has probably the most work done to it: he's actually coming around to the idea of a relationship with Dana Barret (Sigourney Weaver), and her son. Murray's played this type of character through many films (and even more SNL sketches), and it's pleasant to see it developed along the lines it is here. And finally, the Ghostbusters are up against someone rotten enough (and defending someone good enough) that you want to cheer a bit for them. That's perhaps the biggest difference between the two films: GHOSTBUSTERS is more of a "laugh blow-out" movie, while GHOSTBUSTERS II had me leaving the theater feeling good. Amused, too -- there were a lot of jokes I was laughing at during the screening I went to that the audience didn't seem to be reacting too -- but mostly a blanket smile.
Murray and Weaver are particularly good; Murray's scenes with the baby were better than the entire length of THREE MEN AND A BABY. They all react well together. Ramis was fine, Aykroyd a bit muted; Ernie Hudson looked about 5 years younger. I was never crazy about Rick Moranis's character, and I thought it didn't change much from the previous film. And I was a bit disappointed that Annie Potts's character wasn't still hooked up with Igon; I thought they played off one another well. The fellow playing the art director was OK -- I think Billy Crystal's Fernando was really demanded for that part. Finally, Cheech Martin has a tiny role, but he has one of the best lines in the film.
Recommendation: If you don't mind the satiric edge of GHOSTBUSTERS slightly dulled by more attention to the characters, then see it. Not a Totally Excellent film, but quite good and fully entertaining.
Moriarty, aka Jeff Meyer INTERNET<EMAIL_ADDRESS>Manual UUCP: {uw-beaver, sun, hplsla, thebes, microsoft}!fluke!moriarty
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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belongs to the author.
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Related links: index of all rec.arts.movies.reviews reviews


One UI 2.0 Beta 3 update is rolling out for the Galaxy S10 (Update: rolling out in US)
by David OhSamsung kicked off the Android 10 beta program for the Galaxy S10 family last month, and it's already released a couple of updates. Today, there is a new OTA rolling out for the S10s in South Korea and the UK — this will be the third update for Korea, but only the second for the UK and other regions that follow the same cadence. As for the US, there are still no signs of the third update.
The third One UI 2.0 beta update (build ZSK3) for the Galaxy S10 brings along a slew of bug fixes and performance enhancements, enumerated in the screenshot below:
Screenshot from a UK Galaxy S10 on the second beta update (but third for other regions).
In addition to these welcome optimizations, Samsung has also begun the rollout of Samsung Daily, a replacement for Bixby Home the company mentioned during its annual developer conference in San Jose last month. According to our tipster from the UK, Samsung Daily became available on his Galaxy S10 after updating to the ZSK3 beta build and performing app updates inside Samsung's Galaxy Store. For all intents and purposes, Samsung Daily still looks very similar to the older Bixby Home's card interface, which may be a disappointment to some. We have some screenshots of what Samsung Daily looks like below.
In Korea, the rollout of the third beta update has already commenced for the S10e, S10, and S10+. The update has also been spotted in the UK. The US models, however, have yet to receive the update. We will update this post as more regions and models receive the third One UI 2.0 beta update.
Update 1: 2019/11/08 10:52am PST by David Oh
The One UI 2.0 beta 3 update commenced rolling out yesterday afternoon for US Galaxy S10 owners. The size of the download varies depending on the S10 model and carrier SIM card inside the device. On my unlocked Galaxy S10+ with a SIM from Sprint, the size of the update file was 605.67 MB.
Unlike our UK tipster's Galaxy S10, the new Samsung Daily app that replaces Bixby Home was not present in the Galaxy Store. Otherwise, the fixes and enhancements in the US One UI 2.0 beta 3 update are identical to the other regions.
Thanks:
Moshe E
End of Update
Thanks:
Zachary K.
Source:
Samsung Community Forum


DIFFSTAT(1) DIFFSTAT(1) NAME diffstat - make histogram from diff-output SYNOPSIS diffstat [options] [file-specifications] DESCRIPTION This program reads the output of diff and displays a histogram of the insertions, deletions, and modifications per-file. Diffstat is a program that is useful for reviewing large, complex patch files. It reads from one or more input files which contain output from diff, producing a his‐ togram of the total lines changed for each file referenced. If the input filename ends with .bz2, .gz, .lzma, .z or .Z, diffstat will read the uncompressed data via a pipe from the corresponding program. It also can infer the compression type from files piped via the standard input. Diffstat recognizes the most popular types of output from diff: unified preferred by the patch utility. context best for readability, but not very compact. default not good for much, but simple to generate. Diffstat detects the lines that are output by diff to tell which files are compared, and then counts the markers in the first column that denote the type of change (insertion, deletion or modification). These are shown in the histogram as "+", "-" and "!" characters. If no filename is given on the command line, diffstat reads the differ‐ ences from the standard input. OPTIONS -b ignore lines matching "Binary files XXX and YYY differ" in the diff -c prefix each line of output with "#", making it a comment-line for shell scripts. -C add SGR color escape sequences to highlight the histogram. -D destination specify a directory containing files which can be referred to as the result of applying the differences. diffstat will count the lines in the corresponding files (after adjusting the names by the -p option) to obtain the total number of lines in each file. The remainder, after subtracting modified and deleted lines, is shown as "unchanged lines". -e file redirect standard error to file. -f format specify the format of the histogram. 0 for concise, which shows only the value and a single histogram code for each of insert (+), delete (-) or modify (!) 1 for normal output, 2 to fill in the histogram with dots, 4 to print each value with the histogram. Any nonzero value gives a histogram. The dots and individual val‐ ues can be combined, e.g., -f6 gives both. -h prints the usage message and exits. -k suppress the merging of filenames in the report. -l lists only the filenames. No histogram is generated. -m merge insert/delete counts from each "chunk" of the patch file to approximate a count of the modified lines. -n number specify the minimum width used for filenames. If you do not spec‐ ify this, diffstat uses the length of the longest filename, after stripping common prefixes. -N number specify the maximum width used for filenames. Names longer than this limit are truncated on the left. If you do not specify this, diffstat next checks the -n option. -o file redirect standard output to file. -p number override the logic that strips common pathnames, simulating the patch "-p" option. -q suppress the "0 files changed" message for empty diffs. -r code provides optional rounding of the data shown in histogram, rather than truncating with error adjustments. 0 is the default. No rounding is performed, but accumulated errors are added to following columns. 1 rounds the data 2 rounds the data and adjusts the histogram to ensure that it displays something if there are any differences even if those would normally be rounded to zero. -R Assume patch was created with old and new files swapped. -s show only the summary line, e.g., number of insertions and dele‐ tions. -S source this is like the -D option, but specifies a location where the original files (before applying differences) can be found. -t overrides the histogram, generates output of comma separated val‐ ues. -u suppress the sorting of filenames in the report. -v show progress, e.g., if the output is redirected to a file, write progress messages to the standard error. -V prints the current version number and exits. -w number specify the maximum width of the histogram. The histogram will never be shorter than 10 columns, just in case the filenames get too large. ENVIRONMENT Diffstat runs in a portable UNIX® environment. You can override the compiled-in paths of programs used for decompressing input files by setting environment variables corresponding to their name: DIFFSTAT_BZCAT_PATH DIFFSTAT_BZIP2_PATH DIFFSTAT_COMPRESS_PATH DIFFSTAT_GZIP_PATH DIFFSTAT_LZCAT_PATH DIFFSTAT_PCAT_PATH DIFFSTAT_UNCOMPRESS_PATH DIFFSTAT_XZ_PATH DIFFSTAT_ZCAT_PATH However, diffstat assumes that the resulting program uses the same com‐ mand-line options, e.g., "-c" to decompress to the standard output. FILES Diffstat is a single binary module, which uses no auxiliary files. BUGS Diffstat makes a lot of assumptions about the format of a diff file. There is no way to obtain a filename from the standard diff between two files with no options. Context diffs work, as well as unified diffs. There's no easy way to determine the degree of overlap between the "before" and "after" displays of modified lines. diffstat simply counts the number of inserted and deleted lines to approximate modified lines for the -m option. SEE ALSO diff(1). AUTHOR Thomas Dickey<EMAIL_ADDRESS>DIFFSTAT(1)


Want to know who is currently riding a bicycle? Looking for friends nearby? Put yourself on map.
Features & FAQs
How does it work?
The system just determines your physical location at the given moment and puts this info on map and onto the bike-tracking feed.
What info it leaves on the website?
It puts your name, picture and link to Facebook profile together with current time and phisical address. Yes, you need to log-in via Facebook to personalize your experience.
What does log-in via Facebook do?
It requests only you email address and public info. We also hate spam, and your email address will be used only for associating your person in our system. We don't post any messages on your wall and don't keep any passwords.
What about Mobile App?
This website is powered by adaptive design and it easily could be used on your mobile phone or tablet. Try resizing your browser window to see how it works.


nips nips2003 nips2003-146 nips2003-146-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Claire Monteleoni, Tommi S. Jaakkola
Abstract: We consider an online learning scenario in which the learner can make predictions on the basis of a ﬁxed set of experts. We derive upper and lower relative loss bounds for a class of universal learning algorithms involving a switching dynamics over the choice of the experts. On the basis of the performance bounds we provide the optimal a priori discretization for learning the parameter that governs the switching dynamics. We demonstrate the new algorithm in the context of wireless networks.
[1] P. Auer, N. Cesa-Bianchi, Y. Freund, and R. E. Schapire. Gambling in a rigged casino: the adversarial multi-armed bandit problem. In Proc. of the 36th Annual Symposium on Foundations of Computer Science, pages 322–331, 1995.
[2] Berkeley. UC Berkeley home IP web traces. In http://ita.ee.lbl.gov/html/contrib/UCB.homeIP-HTTP.html, 1996.
[3] A. Blum, C. Burch, and A. Kalai. Finely-competitive paging. In IEEE 40th Annual Symposium on Foundations of Computer Science, page 450, New York, New York, October 1999.
[4] D. P. Foster and R. Vohra. Regret in the on-line decision problem. Games and Economic Behavior, 29:7–35, 1999.
[5] Y. Freund and R. Schapire. Adaptive game playing using multiplicative weights. Games and Economic Behavior, 29:79–103, 1999.
[6] D. Haussler, J. Kivinen, and M. K. Warmuth. Sequential prediction of individual sequences under general loss functions. IEEE Trans. on Information Theory, 44(5):1906–1925, 1998.
[7] D. P. Helmbold, R. E. Schapire, Y. Singer, and M. K. Warmuth. On-line portfolio selection using multiplicative updates. In International Conference on Machine Learning, pages 243– 251, 1996.
[8] M. Herbster and M. K. Warmuth. Tracking the best expert. Machine Learning, 32:151–178, 1998.
[9] IEEE. Computer society LAN MAN standards committee. In IEEE Std 802.11: Wireless LAN Medium Access Control and Physical Layer Speciﬁcations, August 1999.
[10] R. Krashinsky and H. Balakrishnan. Minimizing energy for wireless web access with bounded slowdown. In MobiCom 2002, Atlanta, GA, September 2002.
[11] R. Krichevsky and V. Troﬁmov. The performance of universal encoding. IEEE Trans. on Information Theory, 27(2):199–207, 1981.
[12] N. Littlestone and M. K. Warmuth. The weighted majority algorithm. In IEEE Symposium on Foundations of Computer Science, pages 256–261, 1989.
[13] C. Steinbach. A reinforcement-learning approach to power management. In AI Technical Report, M.Eng Thesis, Artiﬁcial Intelligence Laboratory, MIT, May 2002.
[14] V. Vovk. Derandomizing stochastic prediction strategies. Machine Learning, 35:247–282, 1999.


I'm rebranding "letting weeds run away with your garden" as "cultivating composting material." Yessir, gonna be a good year for compost.
8/2/2011, 9:58:57 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
I'm rebranding "letting weeds run away with your garden" as "cultivating composting material." Yessir, gonna be a good year for compost.
8/2/2011, 9:58:57 PM
Favs: 0
Retweets: 0
link


Toggle navigation
POPO voz
VOZ thread
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Eyes
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Bricks
Forked From https://github.com/dangsonbk/vozpopo


Galvanize Delivers
Order Delivery
Menu
Royale with cheese
$8.99
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Smoked swine
$14.99
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{% extends '../layouts/default.html' %} {% block main %}
Pieces are rendered in a certain layer order. Lower layers are drawn below, higher layers are drawn on top. You can also put pieces in the same layer, for example to allow 2 decks of cards to be shuffled/mixed.
{% endif %}


|
iir1
|
#include <Cascade.h>
Public Member Functions | |
| void | reset () |
| void | setup (const double(&sosCoefficients)[MaxStages][6]) |
| template<typename Sample > | |
| Sample | filter (const Sample in) |
| const Cascade::Storage | getCascadeStorage () |
Storage for Cascade: This holds a chain of 2nd order filters with its coefficients.
|
inline |
Filters one sample through the whole chain of biquads and return the result
| in | Sample to be filtered |
|
inline |
Returns the coefficients of the entire Biquad chain
|
inline |
Resets all biquads (i.e. the delay lines but not the coefficients)
|
inline |
Sets the coefficients of the whole chain of biquads.
| sosCoefficients | 2D array in Python style sos ordering: 0-2: FIR, 3-5: IIR coeff. |


Completed {{completed_count}} of {{total_count}} questions ({{(100*completed_count)//total_count}}%)
{% block content %}{% endblock %}


# Copyright 2017 Johns Hopkins University (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import division
import collections
import logging
import math
import six
# chainer related
from chainer import cuda
from chainer import training
from chainer import Variable
from chainer.training.updaters.multiprocess_parallel_updater import gather_grads
from chainer.training.updaters.multiprocess_parallel_updater import gather_params
from chainer.training.updaters.multiprocess_parallel_updater import scatter_grads
import numpy as np
# copied from https://github.com/chainer/chainer/blob/master/chainer/optimizer.py
[docs]def sum_sqnorm(arr):
"""Calculate the norm of the array.
Args:
arr (numpy.ndarray)
Returns:
Float: Sum of the norm calculated from the given array.
"""
sq_sum = collections.defaultdict(float)
for x in arr:
with cuda.get_device_from_array(x) as dev:
if x is not None:
x = x.ravel()
s = x.dot(x)
sq_sum[int(dev)] += s
return sum([float(i) for i in six.itervalues(sq_sum)])
[docs]class CustomUpdater(training.StandardUpdater):
"""Custom updater for chainer.
Args:
train_iter (iterator | dict[str, iterator]): Dataset iterator for the
training dataset. It can also be a dictionary that maps strings to
iterators. If this is just an iterator, then the iterator is
registered by the name ``'main'``.
optimizer (optimizer | dict[str, optimizer]): Optimizer to update
parameters. It can also be a dictionary that maps strings to
optimizers. If this is just an optimizer, then the optimizer is
registered by the name ``'main'``.
converter (espnet.asr.chainer_backend.asr.CustomConverter): Converter
function to build input arrays. Each batch extracted by the main
iterator and the ``device`` option are passed to this function.
:func:`chainer.dataset.concat_examples` is used by default.
device (int or dict): The destination device info to send variables. In the
case of cpu or single gpu, `device=-1 or 0`, respectively.
In the case of multi-gpu, `device={"main":0, "sub_1": 1, ...}`.
accum_grad (int):The number of gradient accumulation. if set to 2, the network
parameters will be updated once in twice, i.e. actual batchsize will be doubled.
"""
def __init__(self, train_iter, optimizer, converter, device, accum_grad=1):
super(CustomUpdater, self).__init__(
train_iter, optimizer, converter=converter, device=device)
self.forward_count = 0
self.accum_grad = accum_grad
self.start = True
# To solve #1091, it is required to set the variable inside this class.
self.device = device
# The core part of the update routine can be customized by overriding.
[docs] def update_core(self):
"""Main update routine for Custom Updater."""
train_iter = self.get_iterator('main')
optimizer = self.get_optimizer('main')
# Get batch and convert into variables
batch = train_iter.next()
x = self.converter(batch, self.device)
if self.start:
optimizer.target.cleargrads()
self.start = False
# Compute the loss at this time step and accumulate it
loss = optimizer.target(*x) / self.accum_grad
loss.backward() # Backprop
loss.unchain_backward() # Truncate the graph
# update parameters
self.forward_count += 1
if self.forward_count != self.accum_grad:
return
self.forward_count = 0
# compute the gradient norm to check if it is normal or not
grad_norm = np.sqrt(sum_sqnorm(
[p.grad for p in optimizer.target.params(False)]))
logging.info('grad norm={}'.format(grad_norm))
if math.isnan(grad_norm):
logging.warning('grad norm is nan. Do not update model.')
else:
optimizer.update()
optimizer.target.cleargrads() # Clear the parameter gradients
[docs] def update(self):
self.update_core()
if self.forward_count == 0:
self.iteration += 1
[docs]class CustomParallelUpdater(training.updaters.MultiprocessParallelUpdater):
"""Custom Parallel Updater for chainer.
Defines the main update routine.
Args:
train_iter (iterator | dict[str, iterator]): Dataset iterator for the
training dataset. It can also be a dictionary that maps strings to
iterators. If this is just an iterator, then the iterator is
registered by the name ``'main'``.
optimizer (optimizer | dict[str, optimizer]): Optimizer to update
parameters. It can also be a dictionary that maps strings to
optimizers. If this is just an optimizer, then the optimizer is
registered by the name ``'main'``.
converter (espnet.asr.chainer_backend.asr.CustomConverter): Converter
function to build input arrays. Each batch extracted by the main
iterator and the ``device`` option are passed to this function.
:func:`chainer.dataset.concat_examples` is used by default.
device (torch.device): Device to which the training data is sent. Negative value
indicates the host memory (CPU).
accum_grad (int):The number of gradient accumulation. if set to 2, the network
parameters will be updated once in twice, i.e. actual batchsize will be doubled.
"""
def __init__(self, train_iters, optimizer, converter, devices, accum_grad=1):
super(CustomParallelUpdater, self).__init__(
train_iters, optimizer, converter=converter, devices=devices)
from cupy.cuda import nccl
self.accum_grad = accum_grad
self.forward_count = 0
self.nccl = nccl
# The core part of the update routine can be customized by overriding.
[docs] def update_core(self):
"""Main Update routine of the custom parallel updater."""
self.setup_workers()
self._send_message(('update', None))
with cuda.Device(self._devices[0]):
# For reducing memory
optimizer = self.get_optimizer('main')
batch = self.get_iterator('main').next()
x = self.converter(batch, self._devices[0])
loss = self._master(*x) / self.accum_grad
loss.backward()
loss.unchain_backward()
# NCCL: reduce grads
null_stream = cuda.Stream.null
if self.comm is not None:
gg = gather_grads(self._master)
self.comm.reduce(gg.data.ptr, gg.data.ptr, gg.size,
self.nccl.NCCL_FLOAT,
self.nccl.NCCL_SUM,
0, null_stream.ptr)
scatter_grads(self._master, gg)
del gg
# update parameters
self.forward_count += 1
if self.forward_count != self.accum_grad:
return
self.forward_count = 0
# check gradient value
grad_norm = np.sqrt(sum_sqnorm(
[p.grad for p in optimizer.target.params(False)]))
logging.info('grad norm={}'.format(grad_norm))
# update
if math.isnan(grad_norm):
logging.warning('grad norm is nan. Do not update model.')
else:
optimizer.update()
self._master.cleargrads()
if self.comm is not None:
gp = gather_params(self._master)
self.comm.bcast(gp.data.ptr, gp.size, self.nccl.NCCL_FLOAT,
0, null_stream.ptr)
[docs] def update(self):
self.update_core()
if self.forward_count == 0:
self.iteration += 1
[docs]class CustomConverter(object):
"""Custom Converter.
Args:
subsampling_factor (int): The subsampling factor.
"""
def __init__(self, subsampling_factor=1):
self.subsampling_factor = subsampling_factor
def __call__(self, batch, device):
"""Perform sabsampling.
Args:
batch (list): Batch that will be sabsampled.
device (device): GPU device.
Returns:
chainer.Variable: xp.array that sabsampled from batch.
xp.array: xp.array of the length of the mini-batches.
chainer.Variable: xp.array that sabsampled from batch.
"""
# set device
xp = cuda.cupy if device != -1 else np
# batch should be located in list
assert len(batch) == 1
xs, ys = batch[0]
# perform subsampling
if self.subsampling_factor > 1:
xs = [x[::self.subsampling_factor, :] for x in xs]
# get batch made of lengths of input sequences
ilens = [x.shape[0] for x in xs]
# convert to Variable
xs = [Variable(xp.array(x, dtype=xp.float32)) for x in xs]
ilens = xp.array(ilens, dtype=xp.int32)
ys = [Variable(xp.array(y, dtype=xp.int32)) for y in ys]
return xs, ilens, ys


Philosophy behind unit systems¶
Dimensions¶
Introduction¶
At the root of unit systems are dimension systems, whose structure mainly determines the one of unit systems. Our definition could seem rough but they are largely sufficient for our purposes.
A dimension will be defined as a property which is measurable and assigned to a specific phenomenom. In this sense dimensions are different from pure numbers because they carry some extra-sense, and for this reason two different dimensions can not be added. For example time or length are dimensions, but also any other things which has some sense for us, like angle, number of particles (moles...) or information (bits...).
From this point of view the only truly dimensionless quantity are pure numbers. The idea of being dimensionless is very system-dependent, as can be seen from the \((c, \hbar, G)\), in which all units appears to be dimensionless in the usual common sense. This is unavoidable for computability of generic unit systems (but at the end we can tell the program what is dimensionless).
Dimensions can be composed together by taking their product or their ratio (to be defined below). For example the velocity is defined as length divided by time, or we can see the length as velocity multiplied by time, depending of what we see as the more fundamental: in general we can select a set of base dimensions from which we can describe all the others.
Group structure¶
After this short introduction whose aim was to introduce the dimensions from an intuitive perspective, we describe the mathematical structure. A dimension system with \(n\) independent dimensions \(\{d_i\}_{i=1,\ldots,n}\) is described by a multiplicative group \(G\):
- there an identity element \(1\) corresponding to pure numbers;
- the product \(D_3 = D_1 D_2\) of two elements \(D_1, D_2 \in G\) is also in \(G\);
- any element \(D \in G\) has an inverse \(D^{-1} \in G\).
We denote
and by definition \(D^0 = 1\). The \(\{d_i\}_{i=1,\ldots,n}\) are called generators of the group since any element \(D \in G\) can be expressed as the product of powers of the generators:
The identity is given for \(a_i = 0, \forall i\), while we recover the generator \(d_i\) for \(a_i = 1, a_j = 0, \forall j \neq i\). This group has the following properties:
- abelian, since the generator commutes, \([d_i, d_j] = 0\);
- countable (infinite but discrete) since the elements are indexed by the powers of the generators [1].
One can change the dimension basis \(\{d'_i\}_{i=1,\ldots,n}\) by taking some combination of the old generators:
Linear space representation¶
It is possible to use the linear space \(\mathbf{Z}^n\) as a representation of the group since the power coefficients \(a_i\) carry all the information one needs (we do not distinguish between the element of the group and its representation):
The change of basis to \(d'_i\) follows the usual rule of change of basis for linear space, the matrix being given by the coefficients \(P_{ij}\), which are simply the coefficients of the new vectors in term of the old basis:
We will use this last solution in our algorithm.
An example¶
In order to illustrate all this formalism, we end this section with a specific example, the MKS system (m, kg, s) with dimensions (L: length, M: mass, T: time). They are represented as (we will always sort the vectors in alphabetic order)
Other dimensions can be derived, for example velocity \(V\) or action \(A\)
We can change the basis to go to the natural system \((m, c, \hbar)\) with dimension (L: length, V: velocity, A: action) [2]. In this basis the generators are
whereas the mass and time are given by
Finally the inverse change of basis matrix \(P^{-1}\) is obtained by gluing the vectors expressed in the old basis:
To find the change of basis matrix we just have to take the inverse
Units¶
Units are constructed upon dimensions: they give them an ordering, or equivalently a magnitude. First one has to choose some origin, usually based on some physical measurement. Then the other units of the same dimensions follow by simple rescaling (we omit for now the case of unit with offset, such as the temperature).
For example consider the length dimension. We start by choosing the origin to be the meter m, and we define the other units from it: the kilometer is \(10^3\) m, the foot is \(0.3048\) m, etc.
After defining several units of different dimensions we can form a unit system, which is basically a dimension system with a notion of scale.
Constants¶
Physical constants are really just units. They indicate that we did not understand that two dimensions are in fact the same. For example we see a velocity for the light different from 1 because we do not think that time is the same as space (which is normal because of our sense; but it is different at the fundamental level). For example, once there was the “heat constant” which allowed to convert between joules and calories since people did not know that heat was energy. As soon as they understood it they fixed this constant to 1 (this is a very schematic story).
We can interpret the fact that now we fix the value of fundamental constants in the SI as showing that they are units (and we use them to define the other usual units).
Quantities¶
A quantity is defined from a factor and a unit. According to this construction, they are very similar to unit since at the very end a quantity is just a scale (made from the quantity and unit factors) and a dimension. What distinguishes units is that they play the role of some fixed references, and we always have a definite number of them.
The need for a reference¶
It is not possible to define from scratch units and unit systems: one needs to define some references, and then build the rest over them. Said in another way, we need an origin for the scales of our units (i.e. a unit with factor 1), and to be sure that all units of a given dimension are defined consistently we need to use the same origin for all of them. This can happend if we want to use a derived unit as a base units in another system: we should not define it as having a scale 1, because, even if it is inconsistent inside the system, we could not convert to the first system since we have two different units (from our point of view) of same scale (which means they are equal for the computer).
We will say that the dimensions and scales defined outside systems are canonical, because we use them for all computations. On the other side the dimensions and scales obtained with reference to a system are called physical, because they ultimately carry a sense.
Let’s use a concrete (and important) example: the case of the mass units. We would like to define the gram as the origin. We would like to define the gram as the canonical origin for the mass, so we assign it a scale 1. Then we can define a system (e.g. in chemistry) that take it as a base unit. The MKS system prefers to use the kilogram; a naive choice would be to attribute it a scale if 1 since it is a base, but we see that we could not convert to the chemistry system because g and kg have both been given the same factor. So we need to define kg as 1000 g, and only then use it as a base in MKS. But as soon as we ask the question “what is the factor of kg in MKS?”, we get the answer 1, since it is a base unit.
Thus we will define all computations without referring to a system, and it is only at the end that we can plug the result into a system to give the context we are interested in.
Literature¶
| [Page52] | C. H. Page, Classes of units in the SI, Am. J. of Phys. 20, 1 (1952): 1. |
| [Page78] | C. H. Page, Units and Dimensions in Physics, Am. J. of Phys. 46, 1 (1978): 78. |
| [deBoer79] | J. de Boer, Group properties of quantities and units, Am. J. of Phys. 47, 9 (1979): 818. |
| [LevyLeblond77] | J.-M. Lévy-Leblond, On the Conceptual Nature of the Physical Constants, La Rivista Del Nuovo Cimento 7, no. 2 (1977): 187-214. |
| [NIST] | NIST reference on constants, units and uncertainties. |
Footnotes
| [1] | In general we will consider only dimensions with a maximum coefficient, so we can only a truncation of the group; but this is not useful for the algorithm. |
| [2] | We anticipate a little by considering \(c\) and \(\hbar\) as units and not as physical constants. |


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Netanyahu's Likud party plans for leadership primaries: media
JERUSALEM (Reuters) - Israeli Prime Minister Benjamin Netanyahu’s Likud party will hold leadership primaries within the next six weeks, Israeli media reported on Sunday.
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public class DoublyConnectedEdgeList
extends java.lang.Object
Upon creation, the vertices
, edges
, and faces
lists are
populated. The vertices
list will have the same indexing as the source Vector2
[].
The edges
list will have edges with the same indexing as the source Vector2
[]
with the exception that twin vertices are stored in odd indices.
Since this implementation only handles simple polygons, only one DoublyConnectedEdgeList.Face
will be created
when the DCEL is created. As more DoublyConnectedEdgeList.HalfEdge
s are added the number of faces will
increase.
DoublyConnectedEdgeList.HalfEdge
s are added to the DCEL via the addHalfEdges(Vertex, Vertex)
method.
It's the responsibility of the calling class(es) to store references to the DCEL vertices. This
can be achieved since the indexing of the vertices
list is the same as the source Vector2
[].
No check is performed to ensure that a pair of DoublyConnectedEdgeList.HalfEdge
s are added that already exist.
| Modifier and Type | Class and Description |
|---|---|
class |
DoublyConnectedEdgeList.Face
Represents a face in the Doubly-Connected Edge List.
|
class |
DoublyConnectedEdgeList.HalfEdge
Represents a half edge of the Doubly-Connected Edge List.
|
class |
DoublyConnectedEdgeList.Vertex
Represents a node in the Doubly-Connected Edge List.
|
| Modifier and Type | Field and Description |
|---|---|
protected java.util.List<DoublyConnectedEdgeList.HalfEdge> |
edges
The list of half edges
|
protected java.util.List<DoublyConnectedEdgeList.Face> |
faces
The list of faces
|
protected java.util.List<DoublyConnectedEdgeList.Vertex> |
vertices
The list of nodes
|
| Constructor and Description |
|---|
DoublyConnectedEdgeList(Vector2[] points)
Full constructor.
|
| Modifier and Type | Method and Description |
|---|---|
void |
addHalfEdges(DoublyConnectedEdgeList.Vertex v1,
DoublyConnectedEdgeList.Vertex v2)
Adds two half edges to this DCEL object given the vertices to connect.
|
java.util.List<Convex> |
getConvexDecomposition()
Returns the convex decomposition of this DCEL assuming that the remaining
faces are all convex polygons.
|
protected DoublyConnectedEdgeList.HalfEdge |
getPreviousEdge(DoublyConnectedEdgeList.Vertex vertex,
DoublyConnectedEdgeList.Face face)
Walks around the given face and finds the previous edge
for the given vertex.
|
protected DoublyConnectedEdgeList.Face |
getReferenceFace(DoublyConnectedEdgeList.Vertex v1,
DoublyConnectedEdgeList.Vertex v2)
Finds the face that both vertices are on.
|
java.util.List<MonotonePolygon<DoublyConnectedEdgeList.Vertex>> |
getYMonotonePolygons()
Returns a list of y-monotone polygons from the faces of this DCEL.
|
void |
hertelMehlhorn()
Performs the Hertel-Mehlhorn algorithm on the given DCEL assuming that
it is a valid triangulation.
|
protected void |
initialize(Vector2[] points)
Initializes the DCEL class given the points of the polygon.
|
protected boolean |
isReflex(DoublyConnectedEdgeList.Vertex v0,
DoublyConnectedEdgeList.Vertex v1,
DoublyConnectedEdgeList.Vertex v2)
Returns true if the given vertices create a reflex vertex.
|
void |
removeHalfEdges(DoublyConnectedEdgeList.HalfEdge edge)
Removes the given half edge and its twin.
|
void |
removeHalfEdges(int index)
Removes the half edges specified by the given interior edge index.
|
protected void |
removeHalfEdges(int index,
DoublyConnectedEdgeList.HalfEdge edge)
Removes the given half edge and its twin.
|
void |
triangulateMonotoneY(MonotonePolygon<DoublyConnectedEdgeList.Vertex> monotonePolygon)
Triangulates the given y-monotone polygon adding the new diagonals to this DCEL.
|
protected java.util.List<DoublyConnectedEdgeList.Vertex> vertices
protected java.util.List<DoublyConnectedEdgeList.HalfEdge> edges
protected java.util.List<DoublyConnectedEdgeList.Face> faces
public DoublyConnectedEdgeList(Vector2[] points)
points
- the points of the simple polygonprotected void initialize(Vector2[] points)
points
- the points of the polygonpublic void addHalfEdges(DoublyConnectedEdgeList.Vertex v1, DoublyConnectedEdgeList.Vertex v2)
This method assumes that no crossing edges will be added.
v1
- the first vertexv2
- the second vertexprotected DoublyConnectedEdgeList.HalfEdge getPreviousEdge(DoublyConnectedEdgeList.Vertex vertex, DoublyConnectedEdgeList.Face face)
This method assumes that the given vertex will be on the given face.
vertex
- the vertex to find the previous edge forface
- the face the edge should lie onDoublyConnectedEdgeList.HalfEdge
the previous edgeprotected DoublyConnectedEdgeList.Face getReferenceFace(DoublyConnectedEdgeList.Vertex v1, DoublyConnectedEdgeList.Vertex v2)
If the given vertices are connected then the first common face is returned.
If the given vertices do not have a common face the first vertex's leaving edge's face is returned.
v1
- the first vertexv2
- the second vertexDoublyConnectedEdgeList.Face
the face on which both vertices liepublic void removeHalfEdges(int index)
This method removes both halves of the edge.
index
- the index of the interior half edge to removepublic void removeHalfEdges(DoublyConnectedEdgeList.HalfEdge edge)
edge
- the half edge to removeprotected void removeHalfEdges(int index, DoublyConnectedEdgeList.HalfEdge edge)
index
- the index of the given edgeedge
- the half edge to removepublic java.util.List<Convex> getConvexDecomposition()
Convex
>public java.util.List<MonotonePolygon<DoublyConnectedEdgeList.Vertex>> getYMonotonePolygons()
This method assumes that all faces within this DCEL are y-monotone and does not perform any verification of this assumption.
MonotonePolygon
>public void triangulateMonotoneY(MonotonePolygon<DoublyConnectedEdgeList.Vertex> monotonePolygon)
monotonePolygon
- the monotone polygon (x or y) to triangulatepublic void hertelMehlhorn()
This method will remove unnecessary diagonals and remove faces that get merged leaving a convex decomposition.
This method is guaranteed to produce a convex decomposition with no more than 4 times the minimum number of convex pieces.
protected boolean isReflex(DoublyConnectedEdgeList.Vertex v0, DoublyConnectedEdgeList.Vertex v1, DoublyConnectedEdgeList.Vertex v2)
v0
- the previous vertexv1
- the vertexv2
- the next vertex


--- layout: post title: "My Week in Review" date: 2019-08-04 22:05:00 +0000 image: https://s3.amazonaws.com/audreywatters/2017-08-06-parrot.jpg imagecredits: https://www.flickr.com/photos/kkanouse/15210475072 ---
This week was mostly about doing additional reading and research in order to fill in some of the gaps in my narrative and analysis.
HEWN, No. 315 via substack.com
Icon credits: The Noun Project


Classic DEVS Wrapper¶
A wrapper for AtomicDEVS models that are to be interpreted as Classic DEVS models
-
class
classicDEVSWrapper.
ClassicDEVSWrapper
(model)[source]¶ Wraps around a normal AtomicDEVS model and intercepts the DEVS specific functions. All attribute read/writes need to be redirected to the model itself.
-
__getattr__
(attr)[source]¶ Fetches the attributes of the model. This is a ‘magic’ function.
Parameters: attr – the attribute to fetch Returns: the fetched attributed
-
__setattr__
(attr, val)[source]¶ Sets the attribute of the model. This is a ‘magic’ function. Only the ‘model’ attribute is not proxied!
Parameters: - attr – the attribute to set
- val – the value to set it to
-
__weakref__
¶ list of weak references to the object (if defined)
-


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Copyright © 2004-2016 W3C® (MIT, ERCIM, Keio, Beihang). W3C liability, trademark and document use rules apply.
This document builds upon on Character Model for the World Wide Web 1.0: Fundamentals [CHARMOD] to provide authors of specifications, software developers, and content developers a common reference on string identity matching on the World Wide Web and thereby increase interoperability.
This section describes the status of this document at the time of its publication. Other documents may supersede this document. A list of current W3C publications and the latest revision of this technical report can be found in the W3C technical reports index at https://www.w3.org/TR/.
This version of the document represents a significant change from the earlier editions. Much of the content is changed and the recommendations are significantly altered. This fact is reflected in a change to the name of the document from "Character Model: Normalization".
Sending comments on this document
If you wish to make comments regarding this document, please raise them as github issues against the latest dated version in /TR. Only send comments by email if you are unable to raise issues on github (see links below). All comments are welcome.
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This document is governed by the 1 September 2015 W3C Process Document.


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"""
State Space Analysis using the Kalman Filter
References
-----------
Durbin., J and Koopman, S.J. `Time Series Analysis by State Space Methods`.
Oxford, 2001.
Hamilton, J.D. `Time Series Analysis`. Princeton, 1994.
Harvey, A.C. `Forecasting, Structural Time Series Models and the Kalman Filter`.
Cambridge, 1989.
Notes
-----
This file follows Hamilton's notation pretty closely.
The ARMA Model class follows Durbin and Koopman notation.
Harvey uses Durbin and Koopman notation.
""" # noqa:E501
# Anderson and Moore `Optimal Filtering` provides a more efficient algorithm
# namely the information filter
# if the number of series is much greater than the number of states
# e.g., with a DSGE model. See Also
# http://www.federalreserve.gov/pubs/oss/oss4/aimindex.html
# Harvey notes that the square root filter will keep P_t pos. def. but
# is not strictly needed outside of the engineering (long series)
from __future__ import print_function
import numpy as np
from . import kalman_loglike
# Fast filtering and smoothing for multivariate state space models
# and The Riksbank -- Strid and Walentin (2008)
# Block Kalman filtering for large-scale DSGE models
# but this is obviously macro model specific
[docs]class KalmanFilter(object):
r"""
Kalman Filter code intended for use with the ARMA model.
Notes
-----
The notation for the state-space form follows Durbin and Koopman (2001).
The observation equations is
.. math:: y_{t} = Z_{t}\alpha_{t} + \epsilon_{t}
The state equation is
.. math:: \alpha_{t+1} = T_{t}\alpha_{t} + R_{t}\eta_{t}
For the present purposed \epsilon_{t} is assumed to always be zero.
"""
[docs] @classmethod
def T(cls, params, r, k, p): # F in Hamilton
"""
The coefficient matrix for the state vector in the state equation.
Its dimension is r+k x r+k.
Parameters
----------
r : int
In the context of the ARMA model r is max(p,q+1) where p is the
AR order and q is the MA order.
k : int
The number of exogenous variables in the ARMA model, including
the constant if appropriate.
p : int
The AR coefficient in an ARMA model.
References
----------
Durbin and Koopman Section 3.7.
"""
arr = np.zeros((r, r), dtype=params.dtype, order="F")
# allows for complex-step derivative
params_padded = np.zeros(r, dtype=params.dtype,
order="F")
# handle zero coefficients if necessary
# NOTE: squeeze added for cg optimizer
params_padded[:p] = params[k:p + k]
arr[:, 0] = params_padded
# first p params are AR coeffs w/ short params
arr[:-1, 1:] = np.eye(r - 1)
return arr
[docs] @classmethod
def R(cls, params, r, k, q, p): # R is H in Hamilton
"""
The coefficient matrix for the state vector in the observation
equation.
Its dimension is r+k x 1.
Parameters
----------
r : int
In the context of the ARMA model r is max(p,q+1) where p is the
AR order and q is the MA order.
k : int
The number of exogenous variables in the ARMA model, including
the constant if appropriate.
q : int
The MA order in an ARMA model.
p : int
The AR order in an ARMA model.
References
----------
Durbin and Koopman Section 3.7.
"""
arr = np.zeros((r, 1), dtype=params.dtype, order="F")
# this allows zero coefficients
# dtype allows for compl. der.
arr[1:q + 1, :] = params[p + k:p + k + q][:, None]
arr[0] = 1.0
return arr
[docs] @classmethod
def Z(cls, r):
"""
Returns the Z selector matrix in the observation equation.
Parameters
----------
r : int
In the context of the ARMA model r is max(p,q+1) where p is the
AR order and q is the MA order.
Notes
-----
Currently only returns a 1 x r vector [1,0,0,...0]. Will need to
be generalized when the Kalman Filter becomes more flexible.
"""
arr = np.zeros((1, r), order="F")
arr[:, 0] = 1.
return arr
[docs] @classmethod
def geterrors(cls, y, k, k_ar, k_ma, k_lags, nobs, Z_mat, m, R_mat, T_mat,
paramsdtype):
"""
Returns just the errors of the Kalman Filter
"""
if np.issubdtype(paramsdtype, np.float64):
return kalman_loglike.kalman_filter_double(
y, k, k_ar, k_ma, k_lags, int(nobs), Z_mat, R_mat, T_mat)[0]
elif np.issubdtype(paramsdtype, np.complex128):
return kalman_loglike.kalman_filter_complex(
y, k, k_ar, k_ma, k_lags, int(nobs), Z_mat, R_mat, T_mat)[0]
else:
raise TypeError("dtype %s is not supported "
"Please file a bug report" % paramsdtype)
@classmethod
def _init_kalman_state(cls, params, arma_model):
"""
Returns the system matrices and other info needed for the
Kalman Filter recursions
"""
paramsdtype = params.dtype
y = arma_model.endog.copy().astype(paramsdtype)
k = arma_model.k_exog + arma_model.k_trend
nobs = arma_model.nobs
k_ar = arma_model.k_ar
k_ma = arma_model.k_ma
k_lags = arma_model.k_lags
if arma_model.transparams:
newparams = arma_model._transparams(params)
else:
newparams = params # don't need a copy if not modified.
if k > 0:
y -= np.dot(arma_model.exog, newparams[:k])
# system matrices
Z_mat = cls.Z(k_lags)
m = Z_mat.shape[1] # r
R_mat = cls.R(newparams, k_lags, k, k_ma, k_ar)
T_mat = cls.T(newparams, k_lags, k, k_ar)
return (y, k, nobs, k_ar, k_ma, k_lags,
newparams, Z_mat, m, R_mat, T_mat, paramsdtype)
[docs] @classmethod
def loglike(cls, params, arma_model, set_sigma2=True):
"""
The loglikelihood for an ARMA model using the Kalman Filter recursions.
Parameters
----------
params : array
The coefficients of the ARMA model, assumed to be in the order of
trend variables and `k` exogenous coefficients, the `p` AR
coefficients, then the `q` MA coefficients.
arma_model : `statsmodels.tsa.arima.ARMA` instance
A reference to the ARMA model instance.
set_sigma2 : bool, optional
True if arma_model.sigma2 should be set.
Note that sigma2 will be computed in any case,
but it will be discarded if set_sigma2 is False.
Notes
-----
This works for both real valued and complex valued parameters. The
complex values being used to compute the numerical derivative. If
available will use a Cython version of the Kalman Filter.
"""
# TODO: see section 3.4.6 in Harvey for computing the derivatives in
# the recursion itself.
# TODO: this won't work for time-varying parameters
(y, k, nobs, k_ar, k_ma, k_lags, newparams, Z_mat, m, R_mat, T_mat,
paramsdtype) = cls._init_kalman_state(params, arma_model)
if np.issubdtype(paramsdtype, np.float64):
loglike, sigma2 = kalman_loglike.kalman_loglike_double(
y, k, k_ar, k_ma, k_lags, int(nobs),
Z_mat, R_mat, T_mat)
elif np.issubdtype(paramsdtype, np.complex128):
loglike, sigma2 = kalman_loglike.kalman_loglike_complex(
y, k, k_ar, k_ma, k_lags, int(nobs),
Z_mat.astype(complex), R_mat, T_mat)
else:
raise TypeError("This dtype %s is not supported "
" Please files a bug report." % paramsdtype)
if set_sigma2:
arma_model.sigma2 = sigma2
return loglike


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The Image Grid
A bunch of beautiful images taken from UNSPLASH.com


--- layout: newsstory title: WE NEEDED THAT match: Yeltz 2 Hastings 1 ---
The mighty Yeltz finished off the year with a much needed 2-1 victory against Hastings. A first half goal from Jason and a winner from Big Rich means we go into 2003 just above the relegation zone in in very tight bottom half of the table.
On New Year's Day we welcome Newport County to Fortress Grove in another game we'll be hoping for maximum points in.
I'm still off on my holidays all week so updates to the site will be a bit slower than usual I'm afraid. Have a very happy New Year, and hopefully I'll see many of you at Dover on January 4th.


Please adjust this slider until the amount of space taken up by the margins looks good.
Some web pages center their content, leaving margins at the sides. We can adjust the zoom to make better use of this space. This will depend on the size of your monitor and your personal preferences.
With increased margins, more of a web page's content will fit on screen at once. With reduced margins, the content will take up more of the screen.


Part 1
2016 General Election - Margin of Victory by County
Percentage Points
Clinton
Trump
> 50%
25%
10%
< 10%
< 10%
10%
25%
> 50%
Source:
Townhall.com
Part 2
2016 General Election - Number of Votes by State
Source:
Townhall.com


Collects all constants in one class
More...
Collects all constants in one class
◆ ChunkSize
| const int FrostweepGames.WebGLPUNVoice.Constants.ChunkSize = SampleRate / 2 |
|
static |
Size of block that sends over network
◆ RecordingTime
| const int FrostweepGames.WebGLPUNVoice.Constants.RecordingTime = 1 |
|
static |
How long will be recorded voice
◆ SampleRate
| const int FrostweepGames.WebGLPUNVoice.Constants.SampleRate = 44100 |
|
static |
Default sample rate of microphone
◆ VoiceEventCode
| const byte FrostweepGames.WebGLPUNVoice.Constants.VoiceEventCode = 199 |
|
static |
Code of network event that uses for voice data transition
The documentation for this class was generated from the following file:
- C:/HOME/PUN2VoiceWebGLUnity/Assets/FrostweepGamesPlugins/WebGLPUNVoice/Scripts/Settings/Constants.cs


{% extends "base.html" %} {% block content %} Welcome to my awesome Blog We Love Django As much as you do..!
We Love Django As much as you do..!
{{ post.user }} | {{ post.created_at }}
{{ post.desc|slice:":200" }}


Before Change
// default algorithm to arpack until we decide that ranomized is preferred
svd_algorithm = "NONE" if quant_sf_only else "ARPACK"
if options["svd_algorithm"] in ["ARPACK", "RANDOMIZED", "NONE"]:
svd_algorithm = options["svd_algorithm"]
logger.debug("Generating compendia for organisms", organism_groups=str(grouped_organisms))
for organism in grouped_organisms:
job = create_job_for_organism(organism, quant_sf_only, svd_algorithm)
After Change
svd_algorithm = options["svd_algorithm"] or "ARPACK"
svd_algorithm_choices = ["ARPACK", "RANDOMIZED", "NONE"]
if options["svd_algorithm"] and options["svd_algorithm"] not in svd_algorithm_choices:
raise Exception("Invalid svd_algorithm option provided. Possible values are " + str(svd_algorithm_choices))
target_organisms = self._get_target_organisms(options)
grouped_organisms = group_organisms_by_biggest_platform(target_organisms)
logger.debug("Generating compendia for organisms", organism_groups=str(grouped_organisms))


The reason there are 2 different palettes is that this palette defines every color that is used. The semantic palette described HOW the colors are used.


In order to help developers formalize responses to NLP Queries, quotek provides a set of structures to store the data.
quotek::nlp::
sentiment
¶Public Members
score
¶stores the computed sentiment score.
sentimentstr
¶Stores whether the computed sentiment is felt overall as positive, negative or neutral. so data stored in here can be “positive”, “negative” or “neutral”
mixed
¶Stores whether the sentiment is felt as mixed or not. If sentiment is mixed, you should take the result carefully.
error
¶Tells if sentiment analysis failed or not
error_message
¶Stores the analysis error message in case of failure
quotek::nlp::
relation
¶Relation structures contain results of machine learning relationship algorithms, which mainly allow to guess “Who does what”. This is a trivial form of summerizing which allows machine processing of complex texts.
quotek::nlp::
action
¶action struct is meant to store detected action for a sentence. Action is composed of 3 components, text (verb) , tense, and negated (if verb is used in its negative form).


Send is a library for streaming files from the file system as a http response supporting partial responses (Ranges), conditional-GET negotiation (If-Match, If-Unmodified-Since, If-None-Match, If-Modified-Since), high test coverage, and granular events which may be leveraged to take appropriate actions in your application or framework.
Looking to serve up entire folders mapped to URLs? Try serve-static.
This is a Node.js module available through the
npm registry. Installation is done using the
npm install
command:
bash
$ npm install send
js
var send = require('send')
Create a new SendStream
for the given path to send to a res
. The req
is
the Node.js HTTP request and the path
is a urlencoded path to send (urlencoded,
not the actual file-system path).
Enable or disable accepting ranged requests, defaults to true.
Disabling this will not send Accept-Ranges
and ignore the contents
of the Range
request header.
Enable or disable setting Cache-Control
response header, defaults to
true. Disabling this will ignore the immutable
and maxAge
options.
Set how “dotfiles” are treated when encountered. A dotfile is a file
or directory that begins with a dot (“.”). Note this check is done on
the path itself without checking if the path actually exists on the
disk. If root
is specified, only the dotfiles above the root are
checked (i.e. the root itself can be within a dotfile when when set
to “deny”).
'allow'
No special treatment for dotfiles.'deny'
Send a 403 for any request for a dotfile.'ignore'
Pretend like the dotfile does not exist and 404.The default value is similar to 'ignore'
, with the exception that
this default will not ignore the files within a directory that begins
with a dot, for backward-compatibility.
Byte offset at which the stream ends, defaults to the length of the file
minus 1. The end is inclusive in the stream, meaning end: 3
will include
the 4th byte in the stream.
Enable or disable etag generation, defaults to true.
If a given file doesn’t exist, try appending one of the given extensions,
in the given order. By default, this is disabled (set to false
). An
example value that will serve extension-less HTML files: ['html', 'htm']
.
This is skipped if the requested file already has an extension.
Enable or diable the immutable
directive in the Cache-Control
response
header, defaults to false
. If set to true
, the maxAge
option should
also be specified to enable caching. The immutable
directive will prevent
supported clients from making conditional requests during the life of the
maxAge
option to check if the file has changed.
By default send supports “index.html” files, to disable this
set false
or to supply a new index pass a string or an array
in preferred order.
Enable or disable Last-Modified
header, defaults to true. Uses the file
system’s last modified value.
Provide a max-age in milliseconds for http caching, defaults to 0. This can also be a string accepted by the ms module.
Serve files relative to path
.
Byte offset at which the stream starts, defaults to 0. The start is inclusive,
meaning start: 2
will include the 3rd byte in the stream.
The SendStream
is an event emitter and will emit the following events:
error
an error occurred (err)
directory
a directory was requested (res, path)
file
a file was requested (path, stat)
headers
the headers are about to be set on a file (res, path, stat)
stream
file streaming has started (stream)
end
streaming has completedThe pipe
method is used to pipe the response into the Node.js HTTP response
object, typically send(req, path, options).pipe(res)
.
The mime
export is the global instance of of the
mime
npm module.
This is used to configure the MIME types that are associated with file extensions as well as other options for how to resolve the MIME type of a file (like the default type to use for an unknown file extension).
By default when no error
listeners are present an automatic response will be
made, otherwise you have full control over the response, aka you may show a 5xx
page etc.
It does not perform internal caching, you should use a reverse proxy cache such as Varnish for this, or those fancy things called CDNs. If your application is small enough that it would benefit from single-node memory caching, it’s small enough that it does not need caching at all ;).
To enable debug()
instrumentation output export DEBUG:
$ DEBUG=send node app
$ npm install
$ npm test
```js var http = require(‘http’) var parseUrl = require(‘parseurl’) var send = require(‘send’)
var server = http.createServer(function onRequest (req, res) { send(req, parseUrl(req).pathname).pipe(res) })
server.listen(3000) ```
```js var http = require(‘http’) var parseUrl = require(‘parseurl’) var send = require(‘send’)
// Default unknown types to text/plain send.mime.default_type = ‘text/plain’
// Add a custom type send.mime.define({ ‘application/x-my-type’: [‘x-mt’, ‘x-mtt’] })
var server = http.createServer(function onRequest (req, res) { send(req, parseUrl(req).pathname).pipe(res) })
server.listen(3000) ```
This is a example of serving up a structure of directories with a custom function to render a listing of a directory.
```js var http = require(‘http’) var fs = require(‘fs’) var parseUrl = require(‘parseurl’) var send = require(‘send’)
// Transfer arbitrary files from within /www/example.com/public/* // with a custom handler for directory listing var server = http.createServer(function onRequest (req, res) { send(req, parseUrl(req).pathname, {index: false, root: ‘/www/example.com/public’}) .once(‘directory’, directory) .pipe(res) })
server.listen(3000)
// Custom directory handler function directory (res, path) { var stream = this
// redirect to trailing slash for consistent url if (!stream.hasTrailingSlash()) { return stream.redirect(path) }
// get directory list fs.readdir(path, function onReaddir (err, list) { if (err) return stream.error(err)
// render an index for the directory
res.setHeader('Content-Type', 'text/plain; charset=UTF-8')
res.end(list.join('\n') + '\n') }) } ```
```js var http = require(‘http’) var parseUrl = require(‘parseurl’) var send = require(‘send’)
var server = http.createServer(function onRequest (req, res) { // your custom error-handling logic: function error (err) { res.statusCode = err.status || 500 res.end(err.message) }
// your custom headers function headers (res, path, stat) { // serve all files for download res.setHeader(‘Content-Disposition’, ‘attachment’) }
// your custom directory handling logic: function redirect () { res.statusCode = 301 res.setHeader(‘Location’, req.url + ‘/’) res.end(‘Redirecting to ‘ + req.url + ‘/’) }
// transfer arbitrary files from within // /www/example.com/public/* send(req, parseUrl(req).pathname, {root: ‘/www/example.com/public’}) .on(‘error’, error) .on(‘directory’, redirect) .on(‘headers’, headers) .pipe(res) })
server.listen(3000) ```


Laboratory experiment advisor, ISAE-Supaéro | 2019
Course: Experimental Project on GNSS, 1st year engineering class (PREX A1)
Teaching assistant, ISAE-Supaéro | 2019
Course: Applied Mathematics, MSc Aerospace Engineering (MAE1)
Teaching asistant, ISAE-Supaéro | 2018
Course: Signal Processing (for Navigation), 1st year engineering class (1A)


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viral viruses human virus library (). different fitness host using differences influenza (Figure allele barcode recombinant MDCK replication sequences Influenza cells sequence used containing multiple package {border-style Cat bird px;} specific #ffffff;} proteins protein CRAN acid based Viral mice strains Illumina Virol, amino avian infected library. time abundance data distances evolutionary high origin profiles relative Fisher IAV RNA USA [], analysis followed hosts phylogenetic (HN) China Viruses analyzed embryonated infection obtained selected Cell IAVs Library Stat−/− allantoic cell cells, changes compared day distance eggs individual levels mouse phenotypic px; reads study tropism viruses. {font-family (Thermo A/Puerto Figure Kit RRID: Scientific, Waltham, approach cellular chicken described final font-size group increased infections interferon lungs manuscript performed phenotypes post-infection previously related similar strain supernatants (Data García-SastreA However, MA) NEP NS-containing NS-mediated PaleseP, Rico// S). Table ability background case clusters double; fluid following gene generated hosts. log models plaque plotted profile protein. response segment selection species strategy tree unique -day-old -week-old A/Shanghai// A/Udorn/ Biol, Data Finally, García-SastreA, Phylogenetic Research animals antiviral available barcoded border-color border-width cluster control diversity efficiently evolution expression factors genes groups included interactions library, lines mice, mix murine observed overall phylogenetically rescue results showed single software solid; supplemented tested. versus viruses, {font-style {font-weight μg/ml < (A) (Varble (input) Analysis B), C.M.-R., CBL/ Canada DNA III Mouse: Multiple R.M.-M., Recombinant Samples Strains Thus, Virology, adapted bold cells. clustering combined comparison consistent context converted correlation courier; dynamics em; events experiments expressed expressing factor factors. functional genome host, identical immune incubated initial innate internal involved mainly mammalian modified number overrepresented pandemic possible post-infection. potential processing provide pt;} region reported represented research result shared tested vivo weight work


Imaginary Island Resort Accommodations
We offer many accommodation options
- Resort Hotel Suites
- Resort Hotel Rooms
- Cabanas
- Hammocks under open air thatched rooves
- Survivalist experience where you sleep in the jungle under whatever you can cobble together


Lake Charles, Louisiana
Bilbo Cemetery
This creepy, yet oddly beautiful cemetery is home to one of the founding fathers of Lake Charles.
This entry is a stub
Help improve Atlas Obscura by expanding Bilbo Cemetery with additional information or photos.
When driving along the I-10 into Lake Charles, LA, turning onto Veterans Memorial Blvd, you can’t help but notice the small cemetery just off the water’s edge. Old crypts and a very large statue of Jesus are visible from the roadway.
Bilbo Cemetery is listed on the National Historic Registry and is the final resting place of the “Father of Lake Charles,” John Jacob Ryan. Although the cemetery appears to be slowly sinking into the lake, it houses around 20 crypts that hold the remains of war veterans dating back to the early 19th-century. There are also a few statues of children located around the cemetery, giving the entire location an extra boost of creepiness.
Know Before You Go
The cemetery doesn't have a sign. You will see the Jesus statue rising up through the trees as you turn onto Veterans Memorial Blvd. The cemetery once had a gate, but it has long since deteriorated. You can walk into the cemetery, but stay along the path.
Visit Louisiana with Atlas Obscura Trips
Shifting Tides: Art in New Orleans
Get to know the art, history, and dynamic culture of New Orleans—and the people who bring it to life.
Learn More »
Community Discussion
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No Comments Yet
Start the discussion.
forum Visit our forums.
Sources
- Bilbo Cemetery Lake Charles, LA 70601 https://maps.google.com?q=Bilbo%20Cemetery,%20Lake%20Charles,%20LA%2070601&ftid=0x863b85b5f2f52a83:0xe64cca1945b1a902&hl=en-US&gl=us


TCustomPaintBox32 is a common ancestor for TPaintBox32 and TCustomImage32 objects.
In addition to properties, inherited from TCustomControl, it provides optimized double buffering. The back buffer is a TBitmap32 object, which stores an image data before flushing it to the screen.
Since TCustomPaintBox32 is double buffered, there is no need to redraw its contents every time the control receives WM_PAINT message, as with standard TPaintBox. The repainting is still required when the control is resized.
[See Also]


Simple Web Server
Cpp
#include "crow.h"
int main()
{
crow::SimpleApp app;
CROW_ROUTE(app, "/")([](){
return "Hello world";
});
app.port(8000).multithreaded().run();
}
Go
package main
import (
"fmt"
"net/http"
)
func main() {
http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
fmt.Fprint(w, "Hello world")
})
http.ListenAndServe(":8000", nil)
}
What This Code Does
The goal is to describe a basic web-server that responds with
the string "Hello, World" to the root path of the server (/
).
What's the Same
Both solutions define a Sinatra/Flask style web-server where a path is matched to a simple lambda to handle the request. Both examples also "block" when spawning the web-service.
What's Different
C++, as of C++-17, does not have any standard networking features and thus no standard libraries for creating web-servers. Crow is a simple 3rd-party framework in the style of Sinatra/Flask for creating simple web apps. Other frameworks such as Boost Beast or Cutelyst also exist to serve this need.
It is worth noting that networking in the standard library is coming via the Networking
TS. This
TS has been published, which essentially
means these features are available in a experimental/beta mode as people try them out allowing for any
minor adjustments before being "written in stone." You can find the status for all specifications on the
ISO CPP website.
Asynchronous networking I/O can also be achieved today with Boost.Asio, which currently follows the Networking TS in it's implementation.


Some MEME Suite programs allow as input a file containing tab-delimited data from analysis of tandem mass spectrometry. Some popular software applications that produce files that are supported by the MEME Suite include:
The basic structure of a tab-delimited PSM File is where each such file consists of a single line containing the tab-separated names of fields, followed by one or more lines giving the corresponding field values. For example:
An example PSM file can be found here.
The supported PSM formats each have a column containing modified peptides, where the modified amino acid (if any) is indicated by a number (weight) following it. The table below gives the appropriate column names and an example peptide containing a modified serine in different PSM formats.
| PSM Program Name | Modified Peptide Column Name | Modified Peptide Format (Example) |
|---|---|---|
| Comet | 'modified sequence' | A.AAAS[167]AAA.G |
| MS-GF+ | 'Peptide' | AAAS+79.9AAA |
| Tide | 'sequence' | AAAS[79.9]AAA |
| Percolator | 'sequence' | AAAS[79.9]AAA |


Watering Schedule
Automatic
3 Hours 5 Minutes / Week
Valves 1, 4
1 Hour / Day
Valve 2
2 Hours 30 Minutes / Week
Valve 3
Custom
Mondays 3:00 PM - 4:00 PM
Valves 2, 3
Add to Watering Schedule
For valves
#1
#2
#3
#4
Turn on water
Water {{item.lower}} for
hours and
minutes every week
Usage
This is the usage section
Help
This is the help section


TechVidya-2k19
Home
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PLAY-TRIX
General rules:-
The team should consist of a maximum of two members.
Participants will not be allowed to use mobile phones or any other electronic gadgets inside the hall.
Any change in the team members should be notified in prior.
Necessities like paper will be provided.
Every round is an elimination round .
The decision of the judge will be final and are not subjected to any further changes.
Description:-
Picsword (visual):-
Rapid fire round.
The participants should guess the word looking at the picture clues given.
Negative points for wrong answers.
Tech charades :-
One of the participants should act and the other participant should guess the word.
Time limit is 3 minutes per word.
Giving clues for letters of the word is strictly not allowed.
Greedy Knight(board game) :-
A chess board with each box consisting of one coin and knight is given to a team.
The team should collect the maximum number of coins where the knight should be moved as per the chess board rules.
The knight cannot be moved to a box without a coin
The time limit for the game will be 2 minutes.
Final round (surprise):- The winners will be announced based on the score they obtain. The rules of the game will be revealed onspot.
Faculty Coordinator:
Prof. Deepika M(8892611523)
Student Coordinator:
Nisarga B -<PHONE_NUMBER>
Amulya P A -<PHONE_NUMBER>


A simple calendar app for scheduling your work day.
7am
8am
9am
10am
11am
12pm
1pm
2pm
3pm
4pm
5pm
6pm
7pm


...a.k.a. "ottokomplete"
Google Rambler attempts to construct a body of text that makes sense from a single seed word, based off of common search queries recommended by Google, which seem to be popular search queries from its users. For example
Check out the source: github.
So, say you're typing in a Google search and start off with the word "house". Google's Autocomplete feature might recommend something like "houses for sale in Boston". Rambler keeps the recommendation, takes the last word, and then puts that back into Google's autocomplete "api" (it's not documented, but it's open). From supplying "boston", it might get back something like "boston red sox suck". Then it'll lookup the word "suck" and so on and so forth.
Rambler tries to improve the quality of the text generated by doing a bit of lexical analysis on it, or sometimes just picking the longest recommendation.
I wanted to see if this would be an effective way to generate sensible text. I thought it might be better than feeding in a book of text into a Markov chain because it uses Google's dataset of popular search queries, which add a human element to it.


--- status: "ready" title: "Ordered list (mixed)" text: "An ordered list with varying list styles for each level (up to three levels deep). Commonly used for terms and conditions or any content that requires clear differentiation." ---
An ordered list:


Sanctuary Activities
At Sanctuary we offer a variety of activities, special to Maui.
All activities listed may be purchased through the main desk in the lobby.
Activities
- Scuba diving lessons (3 hours, $200 per person)
- Snorkeling in a semi-private bay (1 hour, $75 per person)
- Bike tour of the island (4 hours, $100 per person plus bike rental)
- Hike to the highest peak on the island (5 hours, free)
- Traditional Hawaiian luau on a private beach ($80 per person)
Home | Accommodations | Travel Arrangements | Gallery | Contact Us


Anyone pre-ordered or will play it?
I love borderlands
juress
Theme Developer
I will :)
Topicstarter
BrainFooLong
Administrator
I forgot, i pre-ordered, also i will :-)
xXJumpyXx
Helping Hand
I'll get it, I liked the first one :) Not sure about pre-ordering but I'll get it for sure.
José Ortega
Global Moderator
It will be region locked in my country, so...
Topicstarter
BrainFooLong
Administrator
Very great game, tried it and i think it's better than the original.
juress
Theme Developer
brain wrote:
Very great game, tried it and i think it's better than the original.
Handsome Jack is killin' it with his phrases :D
Topicstarter
BrainFooLong
Administrator
Really, great dialogs. But my favourite is claptrap.
Topicstarter
BrainFooLong
Administrator
Sooo, now - After ~30h of gameplay i must say that it is a very, very good game. Better than the original in all things. The whole system is pure motivating.
For all that think about a buy, buy it.
For all that want to add me to steam (maybe for some coop)
http://steamcommunity.com/id/brainfoolong/
juress
Theme Developer
It's awesome, they improved it in every way, but I feel like they didn't really add anything new, which is sad, since the first game was a huge risk and a lot of ppl were saying it's gonna fail.
They totaly should have implemented Diablo 3 loot system, because playing with strangers through matchmaking system must be a pure evil, even with friends it's a ninja loot all the time.
Dendari
Translator
Is the singleplayer better now? I barely played the first one alone because it was very boring (at least for me), so I played it entirely in co-op.
Topicstarter
BrainFooLong
Administrator
I only played single in borderlands and now in borderlands 2 but i definetly gonna try the co-op out soon. So yes, i love both story modes.
Topicstarter
BrainFooLong
Administrator
The story is full of black humor, sarcasm and really bad/good jokes.
xXJumpyXx
Helping Hand
Anyone has the DLCs for the first Borderlands? I've been thinking of getting them for ages but never really went a head and got them.
If you have them, are they good (singleplayer)?
Topicstarter
BrainFooLong
Administrator
I have the GOTY Edition with all DLCs. That's what DLCs meant to be. Very big, funny and completely new content in all DLCs (except Moxxi DLC - It's only the moxxy dome area). That's the reason why i will buy mostly all DLCs for the 2nd part of borderlands.
seniledawdler
Helping Hand
I played the first one through 3 times on xbox with a friend (game corrupted his character while saving so we had to start over after 40h of gameplay). Got the ned, knoxx and the claptrap's revolution dlcs and those were great, although pretty easy if you start them at lvl 50 or something like that (except crawmerax).
Afterwards got the first on ps3 with the dlcs and played them through again.  Moxxi's dlc was pretty boring and didn't waste my time with that. You'll probably get the game of the year edition pretty cheaply nowadays (contains all dlcs).
Started borderlands 2 and it's as good as the first one. Nothing really new, except them explodewhenreloading ammo wasting annoyances, tediore weapons. Love the style still, and the humor. Single player mode seems way too easy, at least in the beginning. I'm only at lvl 15 (with 3 characters) and just rescued that one dude (to not spoil anything). Zero doesn't seem to be a fun single player character at least in the beginning.. again... you can single shot headshot most enemies with sniper on any character.
Liking the badass ranks lots. Preordered my game so waiting for the 5th character. Think I'll get the season pass (access to all 4 dlcs for price of 3) eventually.
Topicstarter
BrainFooLong
Administrator
I am currently at lvl 35 in the second game mode. The single player is quite harder when you reached lvl 30. And the second game mode is also a bit more difficult.
The cool thing is in borderlands, the game scale with your level. You can kill the boss with lvl 25 or lvl 30.


A 2D column vector with 3 elements. More...
#include <b2Math.h>
Public Member Functions | |
| b2Vec3 () | |
| Default constructor does nothing (for performance). | |
| b2Vec3 (float32 x, float32 y, float32 z) | |
| Construct using coordinates. | |
| void | SetZero () |
| Set this vector to all zeros. | |
| void | Set (float32 x_, float32 y_, float32 z_) |
| Set this vector to some specified coordinates. | |
| b2Vec3 | operator- () const |
| Negate this vector. | |
| void | operator+= (const b2Vec3 &v) |
| Add a vector to this vector. | |
| void | operator-= (const b2Vec3 &v) |
| Subtract a vector from this vector. | |
| void | operator*= (float32 s) |
| Multiply this vector by a scalar. | |
Public Attributes | |
| float32 | x |
| float32 | y |
| float32 | z |
A 2D column vector with 3 elements.
| b2Vec3::b2Vec3 | ( | ) | [inline] |
Default constructor does nothing (for performance).
| void b2Vec3::operator*= | ( | float32 | s | ) | [inline] |
Multiply this vector by a scalar.
| void b2Vec3::operator+= | ( | const b2Vec3 & | v | ) | [inline] |
Add a vector to this vector.
| b2Vec3 b2Vec3::operator- | ( | ) | const [inline] |
Negate this vector.
| void b2Vec3::operator-= | ( | const b2Vec3 & | v | ) | [inline] |
Subtract a vector from this vector.
Set this vector to some specified coordinates.
| void b2Vec3::SetZero | ( | ) | [inline] |
Set this vector to all zeros.


code-includes
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Lectus vestibulum mattis ullamcorper velit sed. Sagittis vi. Here is test 1 of code-includes
:
// A test file to be included in
fn fib(n: u32) -> u32 {
match n {
0 => 1,
1 => 1,
_ => fib(n - 1) + fib(n - 2),
}
}
But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system, and expound the actual teachings of the great explorer of the truth, the master-builder of human happiness. Here is test 2 of code-includes
:
// A test file to be included in
fn fib(n: u32) -> u32 {
match n {
0 => 1,
1 => 1,
_ => fib(n - 1) + fib(n - 2),
}
}
Here is Test 3 of code-includes
:
yes
// This should be kept
>>>
please don't fold it
nope.
transclude
beta
:He quickly deduced our goal – ship a quality beta – but he also quickly discerned that we had no idea about the quality of the product because of our pile of untriaged bugs.
gamma
:Gamma rays are ionizing radiation and are thus biologically hazardous. Due to their high penetration power, they can damage bone marrow and internal organs.
the delta
:A river delta is formed at the mouth of a river where the river deposits the sediment load carried by it and drains into a slower moving or static body of water.
Let’s also see if code-includes
still works in the 3rd level of including:
// A test file to be included in
fn fib(n: u32) -> u32 {
match n {
0 => 1,
1 => 1,
_ => fib(n - 1) + fib(n - 2),
}
}
Another test of transclude:
standard-code
some_python = " "
some_python > 0
fun main() {
Sys.Out.Println("Hello World!");
}


--- layout: page title: About header-img: "img/about-bg.png" ---
I am here to share the thoughts on my coding projects.


SLCORRECTRATE Computes the correct rate of classification $ Syntax $ - cr = slcorrectrate(scores, clabels, qlabels, op, ...) $ Arguments $ - scores: the scores to support the classification - clabels: the labels of classes - qlabels: the groundtruth of the labels of query samples - op: the option of the score - cr: the correct rate of the score-based classification $ Description $ - cr = slcorrectrate(scores, clabels, slabels, op, ...) Computes the classification correct rate. Suppose we want to classify n samples into m classes, then scores will be an m x n matrix, with the entry at i-th row, j-th column representing the score of the j-th sample in the i-th class. For op, it can take either of the two values: 'high' and 'low'. If op is 'high' then it means that the sample will be classified to the class where it has the highest score value, vice versa for 'low'. $ History $ - Created by Dahua Lin on Jun 10th, 2005 - Modified by Dahua Lin on May 1st, 2005 - To base on the sltoolbox v4. - Modified by Dahua Lin on Aug 9th, 2006 - Extract slclassify as independent function and base on it - Modified by Dahua Lin on Aug 16th, 2006 - Based on new slclassify to support multiple schemes
0001 function cr = slcorrectrate(scores, clabels, qlabels, op, varargin) 0002 %SLCORRECTRATE Computes the correct rate of classification 0003 % 0004 % $ Syntax $ 0005 % - cr = slcorrectrate(scores, clabels, qlabels, op, ...) 0006 % 0007 % $ Arguments $ 0008 % - scores: the scores to support the classification 0009 % - clabels: the labels of classes 0010 % - qlabels: the groundtruth of the labels of query samples 0011 % - op: the option of the score 0012 % - cr: the correct rate of the score-based classification 0013 % 0014 % $ Description $ 0015 % - cr = slcorrectrate(scores, clabels, slabels, op, ...) 0016 % Computes the classification correct rate. Suppose we want to 0017 % classify n samples into m classes, then scores will be an m x n 0018 % matrix, with the entry at i-th row, j-th column representing the 0019 % score of the j-th sample in the i-th class. 0020 % For op, it can take either of the two values: 'high' and 'low'. 0021 % If op is 'high' then it means that the sample will be classified 0022 % to the class where it has the highest score value, vice versa 0023 % for 'low'. 0024 % 0025 % $ History $ 0026 % - Created by Dahua Lin on Jun 10th, 2005 0027 % - Modified by Dahua Lin on May 1st, 2005 0028 % - To base on the sltoolbox v4. 0029 % - Modified by Dahua Lin on Aug 9th, 2006 0030 % - Extract slclassify as independent function and base on it 0031 % - Modified by Dahua Lin on Aug 16th, 2006 0032 % - Based on new slclassify to support multiple schemes 0033 % 0034 0035 %% parse and verify input arguments 0036 0037 if nargin < 4 0038 raise_lackinput('slcorrectrate', 4); 0039 end 0040 0041 0042 %% Make decision 0043 0044 decisions = slclassify(scores, clabels, op, varargin{:}); 0045 0046 %% Evaluate correct rate 0047 0048 qlabels = qlabels(:)'; 0049 cr = sum(decisions == qlabels) / length(qlabels); 0050 0051 0052 0053 0054 0055 0056


Chapter 3 Advance Design
In this chapter, you will learn how to build your own html templates taken from the web and package them, so that they can be re-used at any time by anybody.
3.1 Selecting a good template
There exists tons of HTML templates over the web. However, only a few part will be suitable for shiny, mainly because of what follows:
- shiny is built on top of bootstrap 3 (HTML, CSS and Javascript framework), meaning that going for another framework might not be straightforward. However, shinymaterial and shiny.semantic are examples showing this can be possible.
- shiny relies on jQuery (currently v 1.12.4 for shiny, whereas the latest version is 3.3.1). Consequently, all templates based upon React, Vue and other Javascript framework will not be natively supported. Again, there exist some examples for React with shiny and more generally, the reactR package developed by Kent Russell ((???) on Twitter) and Alan Dipert from RStudio.
See the github repository for more details about all dependencies related to the shiny package.
Therefore in the following, we will restict ourself to Bootstrap (3 and 4) together with jQuery. Don’t be disapointed since there is still a lot to say.
Notes: As shiny depends on Bootstrap 3.3.7, we recommand the user who would like to experiment Boostrap 4 features to be particularly careful about potential incompatibilies. See a working example here with bs4Dash.
A good source of open source HTML templates is Colorlib and Creative Tim. You might also buy your template, but forget about the packaging option, which would be illegal in this particular case, unless you have a legal agreement with the author (very unlikely however).
3.2 About htmltools
While building a custom html template, you will need to know more about the wonderful htmltools developed by Winston Chang, member of the shiny core team. It has the same spirit as devtools, that is, making your web developer life easier. What follows does not have the pretention to be an exhaustive guide about this package. Yet, it will provide you yith the main tools to be more efficient.
3.2.2 Dependency utilities
When creating a new template, you sometimes need to import custom HTML dependencies that do not come along with shiny. No problem, htmltools is here for you (shiny also contains these functions).
<IP_ADDRESS> The dirty approach
Let’s consider the following example. I want to include a bootstrap 4 card in a shiny app. This example is taken from an interesting question here. The naive approach would be to include the HTML code directly in the app code
library(shiny)
# we create the card function before
my_card <- function(...) {
htmltools::withTags(
div(
class = "card border-success mb-3",
div(class = "card-header bg-transparent border-success"),
div(
class = "card-body text-success",
h3(class = "card-title", "title"),
p(class = "card-text", ...)
),
div(class = "card-footer bg-transparent border-success", "footer")
)
)
}
# we build our app
shinyApp(
ui = fluidPage(
fluidRow(
column(
width = 6,
align = "center",
br(),
my_card("blablabla. PouetPouet Pouet.")
)
)
),
server = function(input, output) {}
)
and desesperately see that nothing is displayed. If you remember, this was expected since
shiny does not contain bootstrap 4 dependencies and this card is unfortunately a
bootstrap 4 object. Don’t panic! We just need to tell shiny to load the css we need to display
this card (if required, we could include the javascript as well). We could use either
includeCSS()
, tags$head(tags$link(rel = "stylesheet", type = "text/css", href = "custom.css"))
. See
more here.
shinyApp(
ui = fluidPage(
# load the css code
includeCSS(path = "https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css"),
fluidRow(
column(
width = 6,
align = "center",
br(),
my_card("blablabla. PouetPouet Pouet.")
)
)
),
server = function(input, output) {}
)
The card is ugly (which is another problem we will fix later) but at least displayed.
When I say this approach is dirty, it is because it will not be easily re-usable by others. Instead, we prefer a packaging approach, like in the next section.
<IP_ADDRESS> The clean approach
We will use the htmlDependency
and attachDependencies
functions from htmltools.
The htmlDependency takes several arguments:
- the name of your dependency
- the version (useful to remember on which version it is built upon)
- a path to the dependency (can be a CDN or a local folder)
- script and stylesheet to respectively pass css and scripts
# handle dependency
card_css <- "bootstrap.min.css"
bs4_card_dep <- function() {
htmltools::htmlDependency(
name = "bs4_card",
version = "1.0",
src = c(href = "https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/"),
stylesheet = card_css
)
}
We create the card tag and give it the bootstrap 4 dependency through the attachDependencies()
function.
# create the card
my_card <- function(...) {
cardTag <- htmltools::withTags(
div(
class = "card border-success mb-3",
div(class = "card-header bg-transparent border-success"),
div(
class = "card-body text-success",
h3(class = "card-title", "title"),
p(class = "card-text", ...)
),
div(class = "card-footer bg-transparent border-success", "footer")
)
)
# attach dependencies
htmltools::attachDependencies(cardTag, bs4_card_dep())
}
We finally run our app:
# run shiny app
ui <- fluidPage(
title = "Hello Shiny!",
fluidRow(
column(
width = 6,
align = "center",
br(),
my_card("blablabla. PouetPouet Pouet.")
)
)
)
shinyApp(ui, server = function(input, output) { })
With this approach, you could develop a package of custom dependencies that people could use when they need to add custom elements in shiny.
3.3 Template Skeleton
Now that you have the basis about tags and dependencies, we can go through the template organisation…
TO DO


PIG-DICE
GET STARTED
Player 1 name :
Player 2 name :
Player 1:
Dice roll:
Round Total:
Total score:
Player 2:
Dice roll:
Round Total:
Total score:


|
||||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |
| Interface Summary | |
|---|---|
| DlogECF2m | Marker interface. |
| DlogECFp | Marker interface. |
| DlogEllipticCurve | Marker interface. |
| DlogGroup | This is the general interface for the discrete logarithm group. |
| DlogZp | Marker interface. |
| DlogZpSafePrime | Marker interface. |
| ECElement | Marker interface. |
| ECF2mPoint | Marker interface for elliptic curve point over the field F2m. |
| ECFpPoint | Marker interface for elliptic curve point over the field Fp. |
| GroupElement | This is the main interface of the Group element hierarchy. |
| GroupElementSendableData | This is a marker interface. |
| primeOrderSubGroup | Marker interface for Dlog groups that has a prime order sub-group. |
| ZpElement | This is a marker interface. |
| ZpSafePrimeElement | This is a marker interface. |
| Class Summary | |
|---|---|
| DlogGroupAbs | DlogGroupAbs is an abstract class that implements common functionality of the Dlog group. |
| DlogGroupEC | This class manages the creation of NIST recommended elliptic curves. |
| ECElementSendableData | |
| ECF2mUtility | This class is a utility class for elliptic curve classes over F2m field. |
| ECFpUtility | This class is a utility class for elliptic curve classes over Fp field. |
| ECParameterSpec | |
| ZpElementSendableData |
|
||||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |


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Projects
Ongoing
Vocodec
A hardware vocal processor, using the Genera Brain for audio DSP and USB-MIDI input. Capable of LPC and channel vocoder effects, autotune, pitch shifting, and formant shifting.
Go to GitHub
Genera Brain
A custom development board for audio DSP, based on the STM32H7 processor and the CS4271 audio codec.
Go to GitHub
LEAF (Lightweight Embedded Audio Framework)
An audio library designed to be lightweight and give control over memory usage and performance for embedded platforms that have limitations in those areas. Written in straight C for portability, with no dependencies. Can be included in JUCE projects for computer and mobile device development as well. (Formerly known as OOPS).
Go to GitHub
Manta
A touch controller with continuous sensor information and LED feedback.
MantaMate
A Eurorack module that allows for communication with the Manta. Turns the Manta into a powerful sequencer and keyboard controller.
Go to GitHub
Drumbox
An electronic percussion instrument using embedded physical modeling synthesis.
Go to GitHub
Birl
An electronic wind instrument with continuous toneholes.
Electrosteel
A synthesizer based on the interface of the pedal steel guitar.
Past Projects
Contravielles
Controllers based on an abstracted string instrument interface.
Bass Manta
A resonator for the Manta controller, inspired by the acoustics of the double bass.
Resophonic Manta
A resonator for the Manta controller, inspired by the design of the resophonic guitar.
Triangle Resonator
An acoustic resonator for electronic sound, with an actuated spruce front and walnut sides and back, and a built in power amplifier.